مقالات رزومه دکتر محمدحسین رضایی مقدم

Morphometric study of a watershed plays a very important role in land structure. Remote sensing methods provide a good tool for studying and extracting stream networks. One of the common methods for extracting waterway networks and conducting a morphometric study of watersheds is the use of Digital Elevation Models (DEMs) with a high spatial resolution. The purpose of this study was to extract stream networks by using the DEMs of high spatial resolution, such as ALOS-1 and Sentinel-1, and those of medium spatial resolution like SRTM and TanDemX. To produce the DEM by using Sentinel-1 images, the InSAR method was applied. Finally, to validate the accuracy of this DEM for checking Sentinel-1 ability to extract stream networks, the ALOS-1 DEM with the spatial resolution of 12.5 m was used. The results revealed that the produced DEMs by using Sentinel-1 images had a high correlation of about 0.99 with the reference data of ALOS-1, thus showing the high capability of the DEM for extracting stream networks. The results of extracting the waterway networks demonstrated that each of the two DEMs of Sentinel-1 and ALOS-1 with high spatial resolutions could extract 9 waterway networks, while the digital models of SRTM and TanDemX with medium resolutions could only extract 7 and 6 stream networks, respectively. The studies indicated that the baseline parameters, as well as the time difference between the two Master and Slave images in InSAR, had to be highly considered by researchers to improve the quality of the Sentinel-1 DEM.

Tectono-karst processes play an important role in the formation and change of landforms. Some areas, such as Zagros in Fars province, are affected by tectono-karst activities due to being in a tectonically active area and also having karstic formations. Due to the importance of studying landform changes in different planning, in this research, the analysis of tectono-karst processes in the formation and expansion of the transverse valleys of Zagros, Fars, from the range of Avaz to Karmostaj has been done. In this research, Sentinel 1 radar images, SRTM 12.5m high digital model, 1:100000 geological map of the region and hydroclimatic information of the region are used as the most important research data. The most important tools used in the research were ArcGIS and GMT. This research has been carried out in two stages according to the desired goals, in the first stage, the tectonic status of the region has been evaluated using the SBAS time series method, and in the second stage, using the Fuzzy Logic-AHP integrated model, to the potential The measurement of areas prone to the development of karstic processes has been discussed. The results obtained from the SBAS time series method have shown that some of the transverse valleys of the region are subsiding in comparison to their downstream regions, and this problem has caused a decrease in the height difference, a decrease in the speed of runoff, creating the necessary opportunity for erosion and dissolution, and in The result is the transverse development of these valleys. Also, based on the results, all the transverse valleys are located in the category with high or very high potential for the development of karstic processes, which indicates the role of karstic processes in the formation of transverse valleys in the region. The total results of this research have shown that the formation and development of transverse valleys in the studied area were affected by tectokarst factors.

The purpose of the present study is to assess the land surface temperature in relation to landuse for the city of Tabriz using remote sensing technology and GIS. Landsat 8 satellite image was used to map the land surface temperature for the study area. Atmospheric correction was applied to the desired image using the FLAASH method and the land surface temperature was estimated using the split-window algorithm for the study area with an accuracy of 1.51 degrees. Landuse map of Tabriz city in 6 classes was obtained using the object-based approach in eCognition software with an accuracy of 90/03. The results of studying the relationship between land surface temperature and landuse indicate that agricultural lands with a temperature of 18.22 °C have the highest land surface temperature. Also, water areas (rivers) have the lowest (10.30 °C) land surface temperature, because of their radiant power close to one. The research results also indicate that the split-window algorithm provides reliable results for land surface temperature estimation that can be used in environmental studies and earth sciences.

Groundwater depletion is one of the scenarios of climate change, which has become a global crisis today. Land use changes and land cover and rapid urbanization are the main causes. The decline of groundwater in recent years has caused land subsidence in many alluvial plains of the country. Uncontrolled and uncontrolled consumption of surface and groundwater resources, reduction of precipitation, concentration of consumption in some places (Imbalance between demand and water supply potential), inadequate cultivation pattern and lack of proper irrigation and digging of multiple wells and operation Irregularity of them in recent decades has caused a critical situation of groundwater resources in most plains of the country. To Groundwater level in most of the country's aquifers is constantly declining and the average annual decline over It has been 12 meters for the last 15 years. Decreasing the groundwater level of the plains increases the cost of water extraction and Increased energy consumption, reduced water quality and the emergence of land subsidence. As side effects, with decreasing volume The phenomenon of subsidence occurs in different spatial and temporal situations with different characteristics such as groundwater content, morphology, pedology and geology, which have different destructive effects. Shabestar-Sufian plain is one of the plains in the northwest of the country, which is facing many restrictions in terms of access to surface water and groundwater and is in a critical situation. In recent decades, the increasing trend of irrigated agricultural lands and overexploitation of groundwater resources has put the plain at risk of subsidence. Groundwater level drop is one of the most common causes of subsidence. Recognizing and examining ways to control it and prevent accelerating the process and expansion of subsidence phenomenon prevents the occurrence of hazards such as groundwater pollution, land slope change, well wall collapse, gradual sinking of masts and structures, changing the slope of rivers and roads Be. Risks that cause significant financial and human losses and on the other hand cause a waste of time and manpower, and pollution and destruction of the environment. In Shabestar-Sufian plain, there may be signs of subsidence in the form of sloping pipes, piping, shallow cavities, which is a warning for this fertile plain. If proper planning is not done regarding the exploitation of groundwater, we will soon see the destruction of lands, houses, water pollution, etc. In this regard,. The aim of this study was to identify areas prone to subsidence, for which the Fuzzy-AHP model was used. Information layers including land slope, altitude, geomorphological units, distance from the river, land use, lithology, groundwater level decline have been used as effective criteria. Expert Choice software was used to perform the calculations and after obtaining the final weights of each criterion, the obtained weight was applied on the layers according to the expert opinions in GIS software. Also, for the fuzzy model, fuzzy maps were combined using the fuzzy gamma operator. To modulate the very high sensitivity of the multiplication fuzzy operator and also the very low sensitivity of the sum fuzzy, the gamma fuzzy operator has been used and finally a map of subsidence prone areas has been prepared. Landslide risk areas are classified into five categories: very low (10.8%), low (14.2%), medium (7.22%), high (7.28%) and very high (2.23%). have became. About 52% of the southern, middle and western regions of the region are at very high risk of landslides due to excessive use of groundwater. In terms of spatial distribution, the highest risk of land subsidence is in the villages of Aq Kahriz, Dizaj Khalil, Shanglabad, Bagherabad, Kafi Malek, Kushk, Hallaji, Yousefabad, Ali Biglou, Haftcheshmeh and Qom Tappeh. Complete and common data were used between 2001 and 2017. Water loss map was prepared by idw interpolation method in gis environment. The results of groundwater status assessments in the region indicate that the study area in recent years has been faced with an increasing trend of groundwater level decline, so that the rate of water level decline has reached 4.7 meters in 18 years, a sharp drop in land subsidence in this region Has caused. . The calculated results are confirmed by examining the time series of water level drop in the wells of the region. Analysis of geomorphological parameters of the region has also shown that the same occurrence of subsidence has been in areas with a slope between zero to 5 valleys, have experienced less subsidence in the slope of more than 5 degrees or no subsidence has occurred in these slopes at all. It has a high subsidence in places with a height of less than 1500 meters, and with salt cover and alluvial materials, as well as areas with agricultural use. Areas close to the river were less prone to subsidence. Flat and smooth slope directions have been the main area of occurrence of this phenomenon. It can be concluded from the results that more than half of the 5% (51%) of the study are prone to high to very high subsidence, this means the critical situation in this plain.

Floods are considered one of the most important and abundant geomorphic hazards in the country, which cause a lot of damage every year. Aji Chai basin, located in East Azerbaijan province, witnesses devastating floods every year due to its large area and special topographical conditions. Therefore, the main aim of this study is to prepare a flood hazard potential map in this basin. To achieve this aim, 18 parameters effective in the occurrence of this hazard and two statistical methods of frequency ratio (FR) and statistical index (SI) have been used. The investigated parameters were Elevation, Slope, Aspect, Rainfall, Distance to the river, River density, Normalized Difference Vegetation Index, land use, Distance to bridge, Distance to dam, lithology, hydrological soil groups, Topographic wetness index, Sediment transport index, Stream power index, Drainage texture, Geomorphology and earth curvature. The location of the past flood points in the area was used to determine the parameters weight and implement the research models. The final maps were prepared from the product of the weights of each parameter class in their information layers and were classified into five classes using the Natural Breaks tool. Study the final maps showed that hazard zones spatial distribution patterns were similar in both models. In this way, the areas downstream of the basin and around the main streams of the area are the most dangerous zones. The accuracy evaluation of the results of both models with the ROC curve showed that the values of the area under the curve for SI and FR models were 0.945 and 0.919, respectively, which shows the excellent performance of both models in preparing flood hazard maps.

Alluvial fans are among the areas prone to geomorphological hazards. One of these hazards is liquefaction, which the main purpose of this research was to investigate this phenomenon in the surface of the alluvial fan. The FUZZY-VIKOR combined model and GIS technique were used to prepare the liquefaction risk potential map. The used parameters in this research were: slope, depth of underground water, type of soil and seismicity. The information layers of each of these parameters were prepared in the ArcGIS software environment. Next, the fuzzy model was used to standardize the layers. At the end, the weighting of the parameters was done by Vikor method. . The results of weighting the parameters by Vikor method showed soil and depth of underground water have obtained the highest importance coefficient with the weight of 0.442 and 0.236 respectively. The final map was prepared by overlapping the layers and multiplying the final weight of the criteria in each layer in 5 classes from very low to very high potential. The final map was prepared by overlapping the layers and multiplying the final weight of the criteria in each layer in 5 classes from very low to very high potential. The results of examining the area of each risk class showed that 0.28% of the area is in the very high class and 70% is in the high class in terms of the risk of liquefaction. Mainly, the areas with high risk potential are located in the downstream parts of the region.

Floods are one of the most destructive natural disasters that cause huge and frequent human losses ,financial and resource losses all over the world(Mishra & Sinha, 2020,1). Flash floods are caused by heavy rains and due to the sudden accumulation and release of runoff from upstream to downstream. This natural phenomenon is the result of the activity of two groups of different parameters. The first group is the meteorological features that change according to space and time. The second group of fixed parameters includes geomorphological and geological characteristics(Youssef et al, 2011,755).Therefore, identification and zoning of areas prone to flood risk is necessary for sustainable development planning and protection of human societies(Farhan & Ayed, 2017, 719). The Ojan Chai basin, which has been flooded in recent years, especially due to human intervention in basin system. One of the most unprecedented floods occurred in this basin in 2016. Therefore, according to the history of flooding in this basin, it is necessary to assess and zoning the risk of sudden flood. The aim of the current research is to evaluate and zoning flash flood-prone areas in the basin based on physiographic characteristics, which is the basis of the modified flash flood potential index (MFFPI).

Aland Chai basin which is located in Khoy County and North West of Iran is one of the high erodibility susceptibility basins due to its unique topographic location and receiving appropriate rainfall throughout the year, especially in spring. The primary purpose of the present study is to investigate and analyze the role of hydrogeomorphic indicators in the sensitivity to erodibility of the sub-basins of the Aland Chai basin located in Khoy County. For this purpose, 12 hydrogeomorphic parameters including Drainage density, Stream frequency, Bifurcation ratio, Drainage texture, Texture ratio, Infiltration Number, Compactness coefficient, Elongation ratio, Circulatory ratio, Form factor, Relief, and Gradient have been used. Study Area Aland Chai basin with an area of 1147.30 km2 is located in the Northwest of Iran and the Western Azerbaijan province. This basin is located between 38°- 30¢-14² and 38°- 48¢-22² N and between 44°- 15¢- 13² and 45°- 01¢-02² E. Basin elevation variations are from 1093m in the Aland Chai River bed to 3638m above sea level in the Avrin Mountain. This basin is one of the sub-basins of the Aras River basin, which surface water flows into the Aras River after joining the grand Qotour River.

In the current study, a geomorphometric ranking method was used considering two groups of hydrogeomorphic parameters to rank the parameters. The first groups are the parameters that have a direct relationship with the erodibility of the sub-basins. These parameters include Drainage density, Stream frequency, Bifurcation ratio, Drainage texture, Infiltration number, Relief, and Gradient. The second group includes 4 parameters of Compactness coefficient, Elongation ratio, Circulatory ratio, and Form factor, which have an inverse relationship with erodibility sensitivity. Next, in order to standardize the geomorphometric rating of each of the parameters, equation 1 is used for the first group and equation 2 for the second group. Equation 1) .Equation 2)

Hydrogeomorphic analysis of basins plays an important role in analyzing the hydrological behavior of basin. In this study, 12 hydrogeomorphic parameters were analyzed from three aspects of drainage network characteristics, shape parameters, and relief characteristics of the basin in order to investigate the role of these parameters in the sensitivity of the Aland Chai basin to erosion. In the next step, the information of each sub-basin based on 22 hydrogeomorphic parameters were prepared using the geomorphological laws of Horton, Schumm, and Strahler in ArcGIS software. In the following, the final map prioritizing the sub-basins in terms of sensitivity to erosion in 5 classes of very high (<43), high (39-42), medium (33-38), low (30-33) and very low (>30) sensitivity was prepared.

The results of erosion susceptibility of sub-basins using hydrogeomorphic parameters also showed that 5 sub-basins (sub-basins 1, 2, 3, 4, and 11) have high susceptibility. Land use changes were investigated in the Aland Chai basin between 1985 and 2020. To prepare a land use map, Landsat time-series images and supervised classification method with Maximum Likelihood Algorithm in ENVI software were used. The results of this part of the study showed that the area of ​​the Rangeland had a decreasing trend between 1985 and 2020. In contrast, with the physical development of Khoy and Firouraq cities during the statistical period under study, we are witnessing an increasing trend in the area of ​​built-up areas. Agricultural and garden classes have also increased in 2000, 2010, and 2020 compared to 1985, but the largest increase in agricultural land and garden area is related to 2000. From 2000 with the physical development of Khoy city (development of settlements and facilities) and the expansion of surrounding villages and the integration of some villages with Khoy city (such as Badal Abad village) and the conversion of agricultural lands into urban areas, we see a downward trend in agricultural lands and gardens. The study of the relationship between land use changes in each sub-basin and their erodibility showed that in the sub-basins upstream of Aland Chai basin, land use change (an increase of agricultural lands) or inappropriate and excessive use of area capacity, it is effective in intensifying erodibility of sub-basins.

The present study investigates and analyzes the role of hydrogeomorphic parameters in flood susceptibility of sub-basins of the Siah Cheshmeh basin located in West Azerbaijan province. For this purpose, first, the study area was divided into 6 sub-basins based on topographic and drainage characteristics using a digital elevation model (DEM) with a spatial resolution of 12.5 m. In the next step, 8 hydrogeomorphic parameters including Stream order, Streams length, Drainage density, Compactness coefficient, Circularity ratio, Form factor, Basin relief and Ruggedness number were prepared using Horton, Schumm, and Strahler geomorphological rules in ArcGIS software. Then, to weight the parameters, the SWARA multi criteria decision-making method was used, and the relative weight of each of the eight parameters was determined for the 6 studied sub-basins. The results of weighting and prioritization showed that sub-basins 2 and 4 with the weight of 0.276 and 0.250, respectively, have the highest weight and have very high flood susceptibility. In contrast, sub-basins 3, and 5 with weights of 0.105, and 0.061, respectively, had the lowest weights in terms of 8 parameters, and therefore, in terms of Flood susceptibility is very low in the class. The total area of the sub-basins that are in high and very high classes (sub-basins 2, and 4) is about 327 Km2, which includes 33.8% of the total area of the basin.

Studying land use changes in the past and predicting these changes for the future is one of the important principles of planning for urban development, management of various hazards, optimal use of natural resources and curbing unprincipled changes in the future. Monitoring and optimal management of natural resources requires timely and correct information. In this regard, land use maps / land cover is one of the most important sources of information in various managements. One of the efficient methods for predicting land cover changes and land use is the Markov chain model. In this study, changes in land cover over the past years and the possibility of predicting it in the future using the Markov chain model in the Zard River basin have been investigated. To achieve this goal, the required satellite images were first prepared using ETM + (2000) ETM +, (2006); ETM + (2012) and OLI-TIRS (2018) sensors; maps were prepared after making corrections on satellite images, and evaluating the accuracy of classifications using kappa coefficient. Then the land use map for 2025 and 2050 is predicted. The results show that if the speed of land use change is the same as in previous years. In 2025, the use of built-up areas will increase to 1089.54 hectares, the use of green space and gardens will decrease to 4/4/2012, the use of wasteland to 85279.59 hectares will be reduce, arable land use will be increased to 1154/52 hectares and surface water use will be increased to 666/54. . In 2050, the use of built-up areas will increase to 1671/98 hectares, the use of green space and gardens will decrease to 192.62 hectares, the use of barren land will decrease to 8438.69 hectares, the use of arable land will increase to 1243.73 hectares. Surface water use will increase to 895.59.

In the beginning of spring, floods are the most important geomorphic hazards in Iran, destructing propertiesas and human lives. Aland Chai basin, located in Khoy County (northwest Iran), is also known as one of the basins with high potential for flood hazard due to its special geographical situation. This study tried to model spatial variation in flood hazard susceptibility in this basin using the ensemble model, FURIA-GA-LogitBoost. For this purpose, 13 effective parameters of flooding including lithology, soil hydrological groups, NDVI, land use, slope, aspect, elevation, distance to the river, river density, precipitation, topographic wetness index, stream power index, and sediment transport index were used. WEKA software was used to implement the research model and the final flood hazard susceptibility map was prepared. The study found that downstream areas of the basin have a high flood hazard susceptibility. These areas contain the most important human settlements (Khoy city) and agricultural lands and flood as a geomorphic hazard can seriously damage them. Considering the ROC curve and area under the curve (AUC), it was found that the FURIA-GA-LogitBoost model performed well in the preparation of flood hazard susceptibility map with coefficients of 0.861 and 0.895, respectively, in training and validation data.

Changes in erosion and sedimentation of the basin are one of the most important factors that affect different parts of human life and natural life. it is very necessary to receive these changes quantitatively, which mainly take place under temperature fluctuations and climate changes in different regions, in order to be more prepared to deal with its negative consequences. In this research, erosion and sedimentation changes in Hajiler watershed were investigated and predicted using GeoWEPP and SWAT models. Based on this, first, by using the data of the current situation of the Ahar synoptic station and using the SDSM model, the changes of the statistical period2020-2040 in three scenarios RCP2.6-RCP4.5-RCP8.5 were investigated, then simulation and prediction of erosion changes was carried out. and sedimentation was done under the influence of climate change by using popular models. The output of the SDSM model indicates an increase in temperature and a decrease in rainfall for the basin until 2040.And the analysis of the simulation results of the sedimentation rate of the models showed that in the studied basin, the GeoWEPP with the selection of the domain method has a suitable level in estimating the sedimentation rate compared to observational statistics. The final model was chosen to predict the amount of sediment in the mentioned period of the basin. Using the downscaled results of the atmospheric general circulation model, the sediment changes in the statistical period of 2020-2040 under the above mentioned three scenarios were estimated as -1.97, 4.45, and 2.98, respectively.

Geodiversity is recognized as an important aspect of nature conservation in itself and is a material consideration in planning decisions in developed countries. In recent decades, many researchers have turned their attention to the definition of geodiversity and its relationship to biodiversity, natural environment protection, ecosystem services, and geotourism. In the emerging science of geodiversity, geomorphodiversity evaluates the shape of the surface features of a place or region. Different geomorphological landforms may occur in a geographical environment that creates a variety of landforms called geomorphodiversity. The purpose of this study is to provide an indicator of geomorphodiversity as an attempt to replace landforms with DEM-derived morphometric parameters and finally to prepare geomorphodiversity maps of the study area; Geomorphodiversity Index (GmI). DEM As the only input data, this approach makes it possible to achieve topographic variables with different horizontal resolution and vertical accuracy and to test more than one topographic data for an area. Thus, the GmI method uses geomorphological data only for result validation and not as input parameters to avoid the limitations mentioned in geomorphological thematic mapping. The Mishu Mountains contain a variety of geomorphological phenomena.
this mountain are less popular today among different regions due to habitat destruction and species extinction. In the past, it was one of the most valuable regions in the country in the regional network and was considered an irreplaceable region. Due to the recent droughts and the lack of codified management plans and also due to the lack of attention in control and supervision of miners and also one of the main conflicts in the Mishu Mountains, we can point to the imbalance between livestock and rangeland. This area has witnessed many destructions over the past years. Mainly the geodiversity of the Misho Mountain region has been involved in its development, providing both opportunities and constraints that need to be managed and understood. With the advent of new approaches in geodiversity, geographical spaces such as Mount Misho can be used effectively.

The study area is located in northwestern Iran. Its highest peak is Ali Alamdar with a height of 3155 meters. In terms of morphological and geological characteristics, it is divided into two parts, Eastern Misho and Western Mishu. In this study, the GMI Quantitative Geomorphodiversity Index presented by Melelli et al. (2017) is used to evaluate. Analysis of indicators and using advanced software such as GIS software, Land Face software and SAGA increases the validity of research findings and results. This analysis includes five factors taken from Melelli et al. The sum of these five parameters shows the geomorphodiversity of the region (Equation 1).
1 : GmI = Geov + Ddv + Rgv + Spv + Lcv
GmI Index of geomorphodiversity:1. Geov is a classified raster map of geological diversity.
2. DdV is a categorized raster map factor for drainage density variability.
3. Rgv Classified raster map is a factor of roughness variation.
4. Spv is a categorized raster map.
5. LcV Classified Raster Map is a factor in Landform classification diversity.
It is necessary to mention that except for the geological map factor, in other factors, the maps went through two stages of processing. The first step is to extract the raw data. The second stage is normalization using natural ruptures. This algorithm reduces the variance within the groups and maximizes the variance between them. Normalization uses the ArcGIS 10.7 reclassification tool to create five classes for each factor. V1 is the lowest while V5 is the highest diversity class (V). This formula is classified into five categories (very low) to (very high). The focus of the research method of this model is the spatial analysis of indicators obtained from Dem 12.5 meters. To evaluate the variability of each parameter, a focal function (neighborhood statistics function) is applied as a result of the variability.

The results of this study showed that the range of geomorphodiversity of the study area decreases from the peaks to the plain and areas with low geomorphodiversity value are located in the plain. The lowest diversity (V1) consists of Quaternary deposits and the highest diversity (V4 and V5) is composed of carbonate formations, intrusive masses, and volcanic formations because they are the rarest type of rocks all over the earth's surface, located mainly in the eastern Mishu. The high values of diversity in the geological factor are related to the erosion-resistant geological substrate (such as volcanic compositions and intrusive masses) and the lowest values of diversity are related to the Quaternary deposits along valleys and plains. The geological factor, waterway network, and landform classification show the highest percentage of area in the upper classes of diversity compared to other parameters of the geomorphodiversity equation (Equation 1). In geological factor due to the large area of carbonate and alluvial assemblies. In the other two factors,

The results of the present study showed that the range of geomorphodiversity of the study area decreases from the peaks to the plain and areas with low geomorphodiversity value are located in the plain. Also, the lowest diversity (V1) consists of Quaternary deposits and the highest diversity (V4 and V5) consists of carbonate formations, intrusive masses and volcanic compounds because they are the rarest type of rocks all over the earth, which are mainly in The eastern parts of Misho are located. The high values of diversity in the geological factor are related to the erosion-resistant geological substrate and the lowest values of diversity are related to the Quaternary deposits along the valleys and plains.The geological factor, waterway network and landform classification show the highest percentage of area in the upper classes of diversity compared to other parameters of the geomorphodiversity equation (Equation 1).

In this study, in order to identify the spatial distribution of soil erosion and sediment production in Sarab Sikan basin, the RUSLE model, GIS and remote sensing technology are used. First, using meteorological data, soil and digital elevation model with a size of 10 meters, each of the factors of erosion erosivity (R), erodibility (K), slope and slope length (LS) and soil protection (P) in the Arc GIS was calculated in Arc GIS. Sentine2 satellite sensor was also used to extract and prepare the vegetation factor of the basin (C) in ENVI 5.3 software environment. Finally, by combining these factors, the amount of basin erosion was calculated and the amount of sediment produced in the basin was obtained by different methods of sediment delivery ratio (SDR). The results showed that the amount of erosion in the basin is varies from 0.003 to 248.4 t ha-1y-1 and the average erosion in the basin is 22.3 t ha-1y-1. Among the model factors, LS factor with a correlation coefficient of R2 = 0.92 showed the highest share in soil erosion. Also, the SDR ratio was calculated by different methods between 0.12 and 0.36, which after combining with the erosion map, the sediment yield of the basin was estimated. The average sediment yield by Boise method is 2.8 t ha-1y-1, which is closer to the amount of station sediment with an average of 1.65 t ha-1y-1 compared to other methods.

Floods and their consequences, with the intensification of human exploitation of nature in the early twentieth century, have had negative effects on vital ecosystems. Also, adverse effects of erosion, while destroying the harvest site, lead to reduced production capacity and degradation of physical and chemical properties of soil in lands. To manage this phenomenon, the factors of production and flood must be identified and then areas with high potential in flood production must be identified to enable the possibility of executive and corrective operations at smaller and risky levels. The level of flood areas in the country is estimated at 91 million hectares, of which about 42 million hectares have moderate to very high flood intensity. Therefore, knowing the flood situation of the regions is a necessity to prepare strategic plans for sustainable management of basins. The purpose of this study is to estimate flood potential and determine the priority of flood areas by physical factors to combat erosion in Hajilar watershed by using a combination of data and information based on the CN-SCS method and also to determine critical flood areas.

In this study, in order to investigate the potential and zoning of flood risk in the basin, at first, by studying and examining the foundations and theoretical background of the subject, the physical factors affecting the occurrence of floods were identified.Then, the required information was collected and layers of each of the proposed factors were prepared in Arc GIS 10.7 software and Arc-Hydro and Arc CN-Runoff extensions. In this regard, the information layers of the waterway network, level lines, and elevation classes were prepared using a digital elevation model with a scale of 1: 120,000. Lithological information layers were obtained using the geological maps of Siah Rud, Tabriz, belonging to the Geological Survey of Iran. The precipitation map of the basin was prepared using data from meteorological stations within the study area and also adjacent stations using IDW interpolation method. Land use layers of the area were obtained using the area land use map and monitoring using Sentinel 2 satellite imagery. The soil map of the region has been prepared using studies of natural resources of Arasbaran basin prepared by the Forests, Rangelands and Watershed Management Organization of the country and controlled with lithological conditions and other environmental factors. Vegetation of the area was prepared through NDVI index. Then, by extracting the number of curves (CN) and the amount of penetration (S), the layers were combined and the runoff height of the basin was estimated by the runoff curve number (CN-SCS) method, the units were classified by SPSS software and the priority of areas in terms of floods in the basin was determined. In order to determine the peak discharge of flood through the obtained data, first based on the proposed Schwab relation, the water accumulation time of all sub-basins was prepared separately and, finally, the maximum peak discharge obtained from this runoff was obtained.

The results of the SCS-CN model which was intended to determine areas with different flood potential in the basin and compare it with environmental factors such as slope, lithology, land use, rainfall, etc in the basin indicate that this model is highly capable of estimating the flood potential in different areas of the basin. Results of changes in the number of curves based on effective environmental factors were also presented in Table 1.The potential for runoff production was high in high altitudes with poor pasture landuse or dryland agriculture with poor permeability soil, as well as in residential areas where the city surface consists of impermeable or low permeability surfaces.Also, there was a high flood potential in the  dense and medium pastures with hydrological group B. Irrigated and rainfed agriculture with hydrological group A has the lowest runoff potential and thus has the lowest amount of flooding in the basin.By obtaining the runoff height in different parts of the basin and determining the levels of changes in the values through quartering, it was found that mainly the central and lower parts of the basin are in the first priorities in terms of flood potential. Poor coverage, low permeability, and low rainfall in this area are some of the factors that increase flood potential. The southern and central regions are areas marked by low sensitivity to flooding. By prioritizing areas in terms of floods and mapping them, the results can be used in watershed management operations at the level of high-sensitivity units to reduce erosion and damage. Taking into account the values of runoff height relative to the sub-basins and water accumulation time obtained based on the Schwab estimation method, the results showed that the flood volume and maximum peak discharge in the basins have a good relationship with each other and the highest maximum peak discharge is related to H33 and H18 sub-basins with volumes of 51.44 and 48.67 and the lowest is related to H12 and H29 sub-basins with volumes of 3.77 and 3.86 m3/s.

Floods are among the most important environmental hazards that cause human and financial losses every year. In the meantime, using the SCS-CN experimental model, as a method for estimating floods in basins with different environmental conditions, and the inter-environmental approach in it can be a useful solution in watershed management studies. Considering that human intervention has caused an increase in floods in all areas, providing methods for accurate flood estimation is one of the basic needs of the relevant responsible organizations. Accordingly, the present study was conducted to determine the priority of areas in terms of flood potential and the results showed that 9% and 51% of the basin areas are in the very dangerous and high-risk flood categories, respectively. According to the final map obtained, Areas with very high risk and high risk are mainly located in residential areas and in the lower areas of the basin, which are the first priority in programs related to water resources, especially flood control and watershed management in the upstream units. Also, according to the results, areas with medium risk potential occupy 23% of the area and 17% of the area has low risk potential. The results of the study confirmed the high potential of the studied area in terms of flood risk, so lands with very high and high risk are lands that should be protected and appropriate watershed management measures must be conducted to control the speed of floods and reduce soil erosion.

 Ecotourism is one of the common types of tourism activities that has attracted a lot of attention in recent years. The ecotourism concept is based on the ideals of environmental protection and sustainable development and refers to a responsible journey to nature with an emphasis on ensuring the improvement of local community life and environmental protection (Seifi and Janbaz, 2017: 479). Ecotourism has a deep connection with sustainable development, which stems from the interactions between tourists and the environment. Proper planning and management in order to develop ecotourism are essential to preserve and maintain the environmental richness of the region as well as the economic improvement of local people (Bunruamkaew and Murayama, 2011: 269). Iran is one of the countries that have a lot of potential for ecotourism development, however, studies show that Iran's natural tourism assets are vast array of scattered, unstabilized resources, and in some cases are on the verge of extinction. The main object of the current paper is to assess the ecotourism potentials and capabilities of the Margavar rural district of Urmia County in northwest of Iran. For this purpose, Analytic Network Process (ANP) and Fuzzy method have been used and ecotourism capabilities zoning map of the study area has been produced.

The current research is a Multicriteria-based study and the Analytic network process (ANP) method and Geographical Information System (GIS) has been used to analyse the data. Spatial criteria were clustered based on reviewing the background into five main groups including climate, human, topography, geology, and tourism and criteria have divided into these 5 groups. At first, the criteria map was prepared in the ArcGIS environment, then all the maps were reclassified with the Reclassify function. In the next step, the criteria maps are standardized with a Fuzzy linear function and the ANP model was run in Super Decisions software, and pairwise comparisons and related super matrices were calculated for the criteria and the relative weight of each criterion was obtained and the resulting weights were applied to maps. Finally, the weighted maps were combined each other using the 0.9 fuzzy gamma operator, and the Fuzzy ecotourism capability zoning map was produced in value 0 to 1.

  After designing the network structure, matrices and related super-matrices were calculated and the relative weights of all criteria were determined. Results showed that temperature, geological structure, slope, rain, and tourism facilities have the most importance and weight in relation to the ecotourism ability of the study area, respectively. According to the ecotourism capabilities zoning map, the study area was divided into four class: completely suitable, relatively suitable, relatively unsuitable, and completely unsuitable. The resulting map analysis shows that areas located in the central and western parts of the region, which have a low slope percentage and also include rich pastures and natural tourist attractions, are in the completely suitable group. Furthermore, some parts of the study area have mountain slopes and difficult topographic conditions that are very difficult to access grouped in completely unsuitable lands for ecotourism activities. The final results of the study show that 14.50% of the study area is in the completely suitable class, 26.32% in the relatively suitable class, 27% in the relatively unsuitable class and 32.15% are in the completely unsuitable class

 Research evaluations show that In general, Margavar rural district, both in terms of potential for the future development of ecotourism and in terms of Its current situation has a lot of potential in this regard in terms of receiving a large number of tourists That comprehensive planning and formulation of effective solutions in this field can be considered an effective way and an important step to achieve sustainable regional development. Application of multi-criteria analysis techniques such as ANP model and Fuzzy model in this research indicates the great flexibility of these methods, which makes it possible to determine different scenarios and combine different criteria with each other. On the other hand, the use of GIS has provided a good platform for feasibility studies, assessment, and identification of the natural environment. Therefore, it can be said that due to the high potential of the Margavar rural district, there is a need to review measures and pay more attention to tourism development plans and studies in this region.

Land subsidence is one of the natural hazards that occurs as a result of natural factors or a combination of these two factors, in the form of flooding. Monitoring land surface changes requires the use of precise techniques. In this regard, the radar interferometry technique with permanent dispersers with wide spatial coverage as well as high temporal and spatial resolution is one of the most accurate and cost-effective remote sensing techniques for monitoring and measuring the amount of displacement on the ground. In recent years, following climate change and successive droughts on the one hand, and the improper management of water resources, improper abstraction of groundwater and increasing growth of population, on the other hand, has led to land displacement - and subsidence, in particular - on the Shabestar-Sufi plain. Therefore, this study has evaluated and monitored the rate of land movement in this region by using the mentioned method and by processing Sentinel-1 images between 2016 and 2020. To study the changes in groundwater level in the region and to prepare a water drop map as well as the hydrograph of the observation wells in the region, water level data between 2001 and 2017 have been used. The results of the permanent dispersion method indicate the annual land displacement rate for the region from 2016 to 2020 in five periods - 8.54, -9.47, 8-9, -9.7 and -9.02 cm, respectively. Due to the lack of geodynamic and GPS stations in the region, validation of the results of the radar interferometry method was assessed by using piezometric well data and the predominance of groundwater level drop (4.7 m) in the region and hydrograph analysis of the aquifer unit, and by comparing the results of the previous research, and the accuracy of the results of the present study was confirmed.

Landslides and slope instability are major hazards to human activity, which cause damage, this instability and hazard are potential and damaging phenomena, our country is mainly mountainous topography, tectonic and seismic activities. The high humidity, diverse geological and climatic conditions have created most of the natural conditions to create a wide range of landslides. The purpose of this study was to identify the effective factors in landslide generation and identify potential landslides in Alamutroud basin in Qazvin province using logistic regression method. In this study, landslide distribution map of the basin was prepared by studying aerial photos and field surveys using GPS and satellite imagery. Eight effective factors including slope, slope direction, sea level rise, distance from riverbed, land use, lithology, distance from fault and drainage network density were used and then processed using Matlab software. , ARC GIS, IDRISI and EXEL. According to the results, 58.26% of the catchment area is in the low and very low risk zone and 17.44% in the high and very high risk area. Also the factors of height and distance from the ranch have the highest scores in landslide creation. Also the model validation indices including pseudo ROC and R_square ChiSquare were calculated /957 -2511/283 and/ 3518  respectively which have acceptable validity.

Land use change is one of the important factors in changing the hydrological flow, basin erosion and biodiversity destruction. Therefore, knowing the effect of land use change on discharge and suspended load is an inevitable necessity. The main purpose of this study is the efficiency test of the model and its usability as a simulation of the process of land use change on discharge and sediment is from the soil and water assessment model (SWAT) and SUFI2 program. Model simulation was performed for 29 years from 1987 to 2015, the first 5 years of which were selected for model calibration and the last 5 years for model results validation. Four statistical indices, r_factor, P_factor Nash-Sutcliffe (NS) and coefficient of determination (R2), the ratio of squared root-to-standard deviation (RSR) and the percentage of skewness (PBIAS) were selected monthly to evaluate the model. The accuracy of monthly simulation using NS evaluation index in the calibration and validation stage for flow and suspended load is equal to 0.65 and 0.49, respectively. The results of the study were considered acceptable according to the interpretive domains used in previous studies and indicate the satisfactory efficiency of the SWAT model in simulating the components of the impact of land use change on sediment and discharge in the Ojan Chay Bostanabad watershed. The results showed that the height of surface runoff increased by 1.15 mm and the sediment concentration increased by 1.5 tons per hectare per year.

Landslides claim the lives of thousands of people around the world each year, causing enormous damage to people and governments. Landslide risk zoning divides landslides into specific and distinct areas of potential and actual degrees in terms of risk, this process is based on recognizing the qualitative characteristics of the area and quantitative modeling based on the data of the study area. This can be the basis for long-term planning at the regional and local levels.The purpose of this study is to investigate and zoning landslide risk in the Yellow River Basin located in the east of Khuzestan province using fuzzy logic method; For this purpose, first through field visits, geological maps and topography and by reviewing previous sources and reviewing the conditions of the region; Nine factors: elevation, slope, direction of slope, distance from fault, distance from river, distance from road, precipitation, lithology and land use were considered and selected as effective factors on landslide occurrence. Landslide hazard zoning maps were prepared using fuzzy gamma operator with values ​​of 0.7, 0.8, 0.9. Then, the obtained maps were classified into 5 classes: very high, high, medium, low and very low.The results of the qualitative sum showed that the 0.9 fuzzy gamma operator is more suitable than other fuzzy operators. The results of the classified maps showed that 21.56% of the area in the high-risk zone and 43.24% of the area The area is located in a low risk zone.

Flood is a disaster which causes a lot of economic damages to farmlands, forests, gas and power transmission lines, roads, engineering structures, and buildings. There are numerous floods in the northwest of country at the beginning of spring and the start of spring rains, which in most cases results in heavy damage [4]. The aim of the present study was to prepare a map of spatial variations in flood risk susceptibility in the Aland Chai basin located in West Azerbaijan province and Khoy city. To achieve this aim, 13 effective parameters in the occurrence of this phenomenon have been used. These parameters include lithology, soil hydrological groups, NDVI, land use, slope, aspect, elevation, distance to river, river density, precipitation, topographic wetness index, stream power index, and sediment transport index.Study areaAland Chai basin is located between 38°- 30¢-14² and 38°- 48¢-22² N and between 44°- 15¢- 13² and 45°- 01¢-02² E in the Northwest of Iran and the Western Azerbaijan province. This basin is one of the sub-basins of the Aras River basin to which surface water flows after joining the grand Qotour River. Basin elevation variations are from 1093m in the Aland Chai River bed to 3638m above sea level in the Avrin Mountain [4].

The following data, software, and methods were used to analysis flood risk susceptibility and prepare flood risk maps in the study area:- A frame of Landsat 8 satellite image OLI scanner with path of 169 and row of 33, in 30m spatial resolution- Geological maps in 1:100000 and 1:250000 scale from Khoy and Dizaj- Topographic map in 1:50000 scale from Khoy city- Digital Elevation Model (DEM) in 12.5m spatial resolution- ArcGIS software to generate maps- ENVI software for land use mapping- WEKA software to data miningThe new ensemble model of FURIA-GA-AdaBoost have been used to investigate the role of parameters in the occurrence of floods. FURIA is a fuzzy rule-based classification method, an extension of the Repeated Incremental Pruning to Produce Error Reduction (RIPPER) rule learner (Cohen, 1995), introduced by Hühn and Hüllermeier (2009) [1, 3]. AdaBoost is a machine learning algorithm introduced by Freund and Schapire in 1997 [2].

To implementation the FURIA-GA algorithm, the following characteristics were obtained after trial and error. For the GA, crossover probability was set to 0.2, mutation probability was set to 0.035, population size at 250, and the number of generations set to 50. For the FURIA evaluator, a 10-fold cross-validation technique with T-Norm product as a fuzzy aggregation operator was trained to combine rule antecedents. The results showed that the FURIA-GA classification with 86.45% was very accurate. The following settings are used to run the AdaBoost algorithm: batchsize, 100; number of iterations, 12; seed, 1. Decision tree C4.5 was also selected as the base classifier. WEKA software was used to perform these algorithms.

The present study was an attempt to investigate the susceptibility of flood risk in the Aland chai basin. Therefore, 13 effective parameters in flood occurrence were used to prepare a flood risk susceptibility map. ArcGIS and ENVI software were used to prepare each of the information layers. In order to perform the relevant analyzes on each of the parameters, the new ensemble model FURIA-GA-AdaBoost in WEKA software was used. The results of these studies showed that slope, soil hydrological groups, altitude, vegetation, and land use have an important role in the occurrence of floods in the area. Flood risk susceptibility map was prepared in 5 classes of very low, low, medium, high, and very high susceptibility. The results showed that the areas that are highly susceptible in terms of flood risk are mainly concentrated downstream of the basin, which includes flat and low areas. Generally, 26% of the total area of the Aland Chai basin is located in high and very high risk for floods.

The history of wars has shown that geomorphology from the largest to the smallest territorial scale at the strategic to tactical level has an effective approach to territorial defense. Environmental factors, such as geomorphology, essentially create the pattern by which military forces must think, plan, and decide to select and implement the best strategy. This study aims to assess the military geomorphology of Jask region and its effect on the territorial defense zoning. In this regard, 15 effective factors were examined and analyzed. To achieve the objectives of the research, 17 questionnaires to use the viewpoints of the defense and geomorphology experts were developed. Super Decision software was used to measure the factors and form the super matrices; and ARC GIS software and FANP model were used to draw the layers and their fuzzy. To prepare the defense geomorphology zoning map, the zoning of the region in 5 defense zones was defined from very unsuitable to very suitable. The results showed that suitable and very suitable areas are the east of Mount Mubarak in west of region to Lirdaf and Bihi in the east; suitable and very suitable zones are along the heights and mountainous areas singularly and separately; and very unsuitable, unsuitable and relatively unsuitable areas are along floodplains, smooth areas and surfaces with rocky outcrops that has no vegetation that leads to vulnerability and increase enemy surveillance.

Landslides are one of the most important environmental hazards to be considered in the Harris Plain area. The phenomenon of subsidence in recent decades has created many problems for agricultural lands, residential areas, roads and water supply canals in some parts of the country. In order to analyze the time series of surface displacement, a short baseline algorithm called SBAS was used. Subsidence time series analysis was performed using 6 interferograms calculated from 21 radar images of Sentinel1 satellite over a period of 4 years (2016-2019). It is an optimal attenuation factor that reduces atmospheric noise, phase recovery error, and orbital effects; in other words, it reduced atmospheric effects using the atmospheric model to optimally maintain nonlinear signals. The results of the time series analysis showed that the region is continuously subsiding. PSI method was also applied to estimate subsidence and compare it with SBAS method, which showed the superiority of SBAS method with PSI method in this study. In this research, using land radar images of Sentinel 1 and also images of Sentinel 2, the land subsidence in Harris plain has been estimated. The land uses in the plain were extracted from Sentinel 2 images and adapted to the results of radar images to investigate the relationship between land subsidence and each of the land uses in the Harris Plain. The results of two methods of estimating land subsidence showed the amount of land displacement (0 to 15) cm per year. The results of depth analysis of piezometric wells also show a strong relationship between subsidence and the depth of water wells in the region.

Subsidence is a morphological phenomenon that occurs under the influence of land subsidence motion. The cause of this phenomenon may be due to human and natural factors. The phenomenon of subsidence in recent decades has created many problems for agricultural lands, residential areas, roads and water supply canals in some parts of the country. In recent years, the decrease in rainfall and the increase in uncontrolled groundwater harvesting by exploitation wells have caused a large drop in groundwater level, which has resulted in subsidence and cracks and fissures in parts of the Harris plain. In this research, in order to determine the affected area and finally estimate the amount of subsidence, the radar interferometer method has been used. The advantages of this method include very high accuracy, wide coverage, high spatial resolution and no need for field work, cost-effectiveness and the possibility of accessing information in any weather conditions. ENVISAT and Sentinel radar satellite images were used for this purpose. Also, two Goldstein and Adaptive filters were used to evaluate the obtained results. Also, to validate the research, the relationship between subsidence and the depth of wells in the region was studied, which showed a positive correlation of 87%; this indicates that the depth of wells is also deeper in the areas where subsidence has occurred.

Software of SARscape5. 2 and SNAP6. 0 used in this research are among the powerful tools for monitoring subsidence. The radar interference method by comparing the phases of two radar images taken from an area in two different times is able to determine changes in the earth's surface in that time period.  The phase obtained from a complication on the ground is proportional to its distance from the radar sensor. Therefore, changing this distance affects the measured phase. An image called an interferogram is created using a radar interferometry technique. To eliminate the topographic effect, the digital elevation model SRTM has been used with a spatial resolution of 90 meters. Orbital errors were modeled by a procedure that have no displacement. Atmospheric error can be adjusted with the help of atmospheric information and atmospheric model. Interferometry is produced by the complex multiplication of one SAR image in the mixed conjugate of the second image. The resulting differential interferometer contains some noise. The cause of these noises can be different, but there are two main factors influencing their occurrence. The first factor is related to the time difference between the two main and dependent images. The second main factor influencing the occurrence of noise is the spatial baseline where the amount of noise in the images is directly related to the spatial baseline. Goldstein and Adaptive Window Filters have been used to remove and reduce noise. As mentioned earlier, Goldstein and Adaptive filters were used in this study, and you will see the main results of these filters below. In principle, the differences between the results of these two widely used filters in the field of radar are discussed. The imageshave been used in the new 2017 to 2019 returns. Coherent image is an image that is resulted from the power correlation of two coordinated images. This image shows the correlation index of signal strength values ​​in two images taken at two different times. The value of correlation varies from 0 to 1, which affects the quality of the interferometry process. After interfrogram processing, to determine the average subsidence rate in the time period of the images, the time series analysis method was used with the least squares method. Based on this, the average subsidence rate is equal to 1. 2 cm. Due to subsidence in this area, it is possible to use groundwater resources indiscriminately and reduce rainfall, which has led to a drop in groundwater levels. Of course, the type of cultivation in the region and the weight pressure caused by human structures in this area can be other causes of subsidence. The obtained results showed that the Goldstein filter has subsidence values ​​up to 9 cm in certain ranges and the uplift values ​​up to about 8. 5 cm and the Adaptive filter subsidence has values ​​up to 9. 5 cm in the range and the values ​​of the uplift up to about 8 cm. The reason for the difference in values ​​ is the results of these two filters. The Goldstein filter, by manipulating the phases, increases the coherence and the brightness of different parts and is higher and brighter, so the situation is better in this filter. In Adaptive filter, phases are not manipulated, coherence zones remain and the amount of blur is greater in different parts of the image. However, in each picture, the amount of subsidence is significantly observed in the east of the area, which is due to the greater concentration of agricultural activity and the use of groundwater.

There is a close relationship between geological formation and subsidence: the weaker the formation, the more noticeable the subsidence in the area. As can be seen, the subsidence in the alluvial formation is more than the volcanic conglomerate formation and the reason is the hardness of the conglomerate stone. As a result, alluvial rocks, andesite and marl have the most subsidence and latite (volcanic) have the least subsidence. Given that the hypothesis of this research was based on the principle that increasing the amount of groundwater extraction causes subsidence in the region, the relationship between the depth of wells in the area and the amount of subsidence in that area can be a good indicator to assess the accuracy of operations. Therefore, the statistics of piezometric wells in the region have been received from the Regional Water Organization of East Azerbaijan Province. After converting it to Arch GJS software database format, the relationship between subsidence values and piezometric well depths was established using zonal spatial analysis functions. Regression correlation analysis between these two factors showed a positive correlation of 87% between them and the implication is that any place that has a lot of subsidence in it is deeper piezometric wells. This finding confirms the hypothesis of this research that there is a direct and strong relationship between subsidence and groundwater abstraction.

The use of radar interference method in this study introduces a good capacity for its capabilities in determining the amount of subsidence in the study area. Findings from the use of this method showed a relatively high rate of subsidence for about a year. According to the maps, the maximum and minimum subsidence in the mentioned periods are 9.8, 0.6 cm, respectively. After entrophagram processing, time series analysis method with least squares method was used to determine the average  subsidence rate in the time period of the images. Based on this analysis, the average subsidence rate is equal to 1.2 cm. One of the causes of subsidence in this area is the indiscriminate use of groundwater resources and reduced rainfall, which has led to a drop in groundwater levels. In the present study, after initial processing on Sentinel-1 satellite data in remote sensing software and GIS, the amount of subsidence in this plain was estimated. Also in this study, both Goldstein and Adaptive filters were used for conducting further investigation. The obtained results indicated that the Goldstein filter has subsidence values up to 9 cm in certain ranges and the uplift values up to about 8.5 cm and the Adaptive filter has the subsidence values up to 9.5 cm in some ranges and uplift values are also shown up to about 8 cm. The reason for the difference in values in the results of these two filters is that the Goldstein filter, by manipulating the phases, increases the coherence rate and the brightness of different parts and the image is brighter, so the situation in this filter improves. But this is not the case with the Adaptive filter, and the phases are not manipulated, and in some areas the coherence remains, and the amount of blur is greater in different parts of the image. However, in both images, the amount of subsidence can be seen significantly to the east of the area, which is due to the greater concentration of agricultural activity and the use of groundwater.

Floods are one of the most common natural hazards, causing significant loss of life and property each year. The purpose of this study is to determine the risk areas of floods in Shahr Chai Miyaneh watershed. To implement this model, different layers such as slope, aspect, elevation, distance from river, river density, land use, vegetation, lithology, rainfall and soil were used. The final analysis and modeling was performed using the Vikor model. The results showed that rainfall, slope and distance from the river have the greatest impact on the occurrence of floods in this watershed. Also, according to the obtained results, 5.2 and 1021.7 square kilometers, respectively, are located in a very high-risk and high-risk area. Dangerous and very dangerous areas are mainly located along the main river and mountainous in the steep logic. Due to the high slope and height of the region, it plays an effective role in the amount of runoff and flow peak floods. Also, in the catchment area of Miyaneh Chai city, 2.2, 27.2, 1099.6, 1021.7 and 10.2 square kilometers, respectively, are in a very low risk, low risk, medium, high risk and very high risk area.